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Reading Dynamics and Comprehension in Cognitive Aging: A Multimodal Language Resource

Summary

The authors present ReMind, an Italian resource that captures how older adults read and understand texts. Its goal is to help detect cognitive decline early, and it addresses the shortage of fine-grained, multimodal reading data for aging populations outside English. Eighty-nine native speakers took part. Clinical assessment placed each of them in one of four groups: cognitively healthy controls (HC), people reporting subjective cognitive decline (SCI), those with Mild Cognitive Impairment (MCI), and those with mild dementia (CDR1). Participants read two adapted Focus magazine texts, silently and aloud, on a tablet running the ReadLet app. The app logs finger movement along the text as a stand-in for eye tracking and also records audio. After reading, participants answered wh-, inferential, referential, and lexical comprehension questions.

The authors used descriptive statistics and GAM regressions to choose features, then tested those features with clustering and supervised classification. Reading speed separated the clinical groups and was also shaped by cognitive reserve, measured as education level. An XGBoost model distinguished unimpaired from impaired participants with moderate success. The resource matters because it provides an inexpensive, scalable, ecologically valid protocol for language-based cognitive screening.

Key points

  • Participants: 89 people (ages 57–88): 38 HC, 9 SCI, 29 MCI, 13 CDR1, all assessed at Pisa University Hospital.
  • Study design: The protocol has three sessions six months apart. Results reported here come from the first session only.
  • Group differences: Dunn's tests with Bonferroni correction showed group differences in comprehension accuracy and in the ratio of silent to aloud reading speed.
  • GAM results: Models of reading speed explained 32.4% of deviance for silent reading and 14.8% for aloud reading.
  • Classification: XGBoost separated CDR0 (HC+SCI) from CDR>0 (MCI+CDR1) using repeated 5-fold cross-validation with 50 repeats. Macro F1 was 0.78. Reading-speed features dominated variable importance.
  • Data release: Anonymised, token-level tabular data are available on Zenodo (doi:10.5281/zenodo.18927776). Fields include tracking duration, onset time, word length and frequency, group, reading mode, and comprehension accuracy. Raw audio is excluded for privacy reasons.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/3wjy3a8cwnw8

@inproceedings{marzi2026reading,
  title = {{Reading Dynamics and Comprehension in Cognitive Aging: A Multimodal Language Resource}},
  author = {Marzi, Claudia and Boni, Noemi and Todesco, Alice and Nadalini, Andrea and Albertin, Giorgia and Dolciotti, Cristina and Bongioanni, Paolo and Ferro, Marcello and Tamburini, Fabio and Gagliardi, Gloria and Pirrelli, Vito},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/3wjy3a8cwnw8},
  url = {https://doi.org/10.63317/3wjy3a8cwnw8}
}

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